Importantly, the opinion reiterates that “courts leave it to the parties to decide how best to respond to discovery requests” and that courts are “not normally in the business of dictating to parties the process that they should use”.

Importantly, Judge Peck instructed that requesting parties can utilize other means to help ensure TAR training, even without production of seed sets. For instance, the honorable Judge suggested statistical estimation of recall towards the end of the review to determine potential gaps in the production of documents.

According to the Grossman-Cormack glossary of technology-assisted review with foreword by John M. Facciola, U.S. Magistrate Judge, seed set is “The initial Training Set provided to the learning Algorithm in an Active Learning process. The Documents in the Seed Set may be selected based on Random Sampling or Judgmental Sampling. Some commentators use the term more restrictively to refer only to Documents chosen using Judgmental Sampling. Other commentators use the term generally to mean any Training Set, including the final Training Set in Iterative Training, or the only Training Set in non-Iterative Training”. The important thing to know about seed sets is that they are how the computer learns. It is critical that a seed set is representative and reflects expert determinations.

As an attorney, I love a good argument corroborated as well as substantiated by solid precedents. Use of TAR in e-Discovery invariably is becoming a matter of “convenience” between both parties in trying to resolve issues. Well, we have arbitration laws for that matter!